Cloud computing smart solar configurator

ABSTRACT

Systems, methods and non-transitory computer-readable storage mediums are disclosed for cloud computing engineering, solar PV (SPV) or solar PV with storage (SPV/S) system configuration, pricing, quoting, advertising messaging, sales lead generation, and content marketing.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. application Ser. No.17/099,176, filed Nov. 16, 2020, which is a continuation of U.S.application Ser. No. 15/896,897, filed Feb. 14, 2018 and issued as U.S.Pat. No. 10,839,436 on Nov. 17, 2020, which claims priority to U.S.Application Ser. No. 62/459,277, filed on Feb. 15, 2017.

TECHNICAL FIELD

The subject matter of this application relates generally to cloudcomputing applications.

BACKGROUND

Customer acquisition costs are extremely high for the solarphotovoltaics (PV) industry. That is, current methods and technologieshave failed to efficiently identify and target customers, and newcustomer groups are not being sufficiently enabled (e.g., communitysolar). Moreover, sales-people are not effectively educating peopleabout the opportunity or the opportunity is not compelling enough, andthis cumbersome and confusing process is resulting in lost sales. Forubiquitous solar to be achieved, new low cost methods of identifying,educating, and selling to millions of customers will need to bedeveloped for residential, mid and large-scale solar installations, andcustomers that range from individuals, to non-profits, to majorcorporations.

For the solar PV industry, the cost of customer acquisition continues torise as the market moves beyond early adopters. The cost and length ofcustomer acquisition are increasing as fewer early mover customersremain, and this challenge is limiting growth. Existing technologies andmethods to improve market transparency and the consumer experience havebeen inadequate, and aggressive marketing practices by the solarindustry continue as current methods are failing at both providingviable leads to dealers and at empowering consumers with the tools theyneed to make informed choices.

Existing solar PV marketing solutions and match-making platforms rely onsimple algorithms that can at best present very generic systemrecommendations with wildly varying costs that only serve to create moreconsumer confusion and skepticism. In fact, current state-of-the-artplatforms simply facilitate installer bids for consumers to choose from.Such methods are not working.

Other popular solar PV system sizing solutions are geared towardoff-line studies for researchers and energy economics experts, and offerno bill of materials (BOM) or detailed engineering evaluationcapabilities, and other applications while providing greater accuracy intechnical evaluation and costs, are not coupled to local load or ratedata to expedite user evaluation.

Some of the challenge is that solar PV model, size and configurationoutputs depend on user inputs, and such inputs may be unknown to theuser, particularly if that person is a ratepayer seeking to installsolar. Attempts to mitigate this challenge by current solar PVevaluation services have had poor results. That is, the consumer solarPV sales experience needs to deliver the same transparency today's PC,laptop, and car buying experience offers consumers, and avoid theopaqueness of the bid facilitating purchasing process, such as Expedia™,where customers have no idea what the person next to them has paid forthe same airline seat.

Today's solar PV system customer acquisition methods continue to offerminimal pricing transparency. This places the solar PV developer incontrol of the discussion (and often the decision) for systemconfiguration design and sizing. Indeed, the distance separating theratepayer from the electric power utility (or technology vendor)facilitates a space for solar PV developers to push certain packages outof economic self-interest without disclosing all options to theratepayer that may have improved performance or economics.

Requiring solar PV shoppers to rely on the very same salespeople theydistrust for information on such large purchase decisions is anuntenable situation if the solar PV industry is to grow past earlyadopters toward ubiquity.

Consumers are seeking solutions to simplify the solar-buying experience,and to achieve confidence in the prices they are quoted by installers.The need to eliminate the hassles of the solar-buying experience in thesame manner TrueCar™ and Kelly Blue Book™ have for the car buyingexperience is one of the key innovations needed to achieve ubiquitoussolar PV energy.

BRIEF DESCRIPTION OF THE DRAWINGS

Features, aspects, and embodiments are described in conjunction with theattached drawings.

FIG. 1 is an illustration of an example Smart Solar Configurator logicflow in accordance with an embodiment.

FIG. 2 is an illustration of example business logic, data models, andoptimization and simulation analytics informing the configurator userinterface described in FIG. 1, in accordance with an embodiment.

FIG. 3 is an illustration of a flowchart describing an example methodfor advertising messaging that is based on value added collaborationbetween a solar PV system dealer or installer (advertiser) and a solarPV system planner (buyer) in order to create a new lead generationadvertising model and quoting by advertiser on system(s) configured bybuyer in accordance with an embodiment.

FIG. 4 is an illustration of a flowchart describing an example methodfor advertising messaging that is based on value added collaborationbetween a vendor (advertiser) and a solar PV planner (buyer) in order tocreate a new “advice” model advertising and direct marketing ofincentives in accordance with an embodiment.

FIG. 5 is a block diagram of example computer architecture forimplementing the features and processes described in reference to FIGS.1-4, according to an embodiment.

For a more complete understanding of the principles disclosed herein,and the advantages thereof, reference is now made to the followingdescriptions taken in conjunction with the accompanying drawings.

DESCRIPTION

Systems, methods and non-transitory computer-readable storage mediumsare disclosed for cloud computing engineering, virtual solar PV (SPV) orsolar PV with storage (SPV/S) system configuration, pricing, quoting,advertising messaging, sales lead generation, and content marketing.

According to one aspect, a method to automatically configure virtual SPVor SPV/S systems for residential and commercial applications comprises:a time-series (e.g., 1 year at 1 minute resolution) power flow circuitmodel and simulator, snap-shot (single time-step) power flow circuitmodel and simulator, economic optimization solver, physically-basedeconomic optimization model, business logic, interactive 2-dimensional(2D) or three-dimensional (3D) product configurator and visualization,logic rules and workflows, techno-economic data models, SPV/S technologyvendor catalog database, market tariffs and incentives database,property electrical energy consumption data, and location atmosphericdata.

In some implementations, a method comprises: displaying, by a computingdevice, a user interface for the user configuration, pricing and quotingof a virtual SPV or SPV/S system for a computer analysis of a virtualSPV or SPV/S; receiving, by the user interface element, user selectionof Objective Function, Constraints, Location, Technologies, Costs, andLoads.

According to one aspect, the Objective Function can be energy costminimization such that: A) energy balance is preserved (e.g. energysupply=energy demand), B) technologies operate within physicalboundaries (e.g. power output <=max output), and C) financialconstraints are verified (e.g. savings obtained by use of the newvirtual SPV or SPV/S must generate savings that repay investments withinthe user defined maximum payback period).

According to another aspect, the Objective Function can be CarbonDioxide emission minimization such that: A) energy balance is preserved(e.g. energy supply=energy demand), B) technologies operate withinphysical boundaries (e.g. power output <=max output), and C) financialconstraints are verified (e.g. savings obtained by use of the newvirtual SPV or SPV/S must generate Carbon Dioxide emission savings thatrepay investments within the user defined maximum payback period).

According to one aspect, the Constraints can be financial boundariessuch as the user's desired maximum payback period or investment timehorizon.

According to another aspect, the Constraints can be physical boundariessuch as the maximum rated electrical current (ampere) carrying capacityof cables, wires, transformers and other power delivery equipment thatmake up the electrical circuit the virtual SPV or SPV/S system willinterconnect or integrate with.

According to another aspect, the Constraints can be operating boundariescalculated by power flow simulation such as energy losses and loading,or “hosting capacity” of existing cables, wires, transformers and otherpower delivery equipment that make up the electrical circuit the PVS/Ssystem will interconnect or integrate with.

According to another aspect, the Constraints can be operating boundariessuch as the allowable voltage drop at each node in the electricalnetwork the virtual SPV or SPV/S system in two-dimensions orthree-dimensions.

In some implementation, a method comprises: displaying, by a computingdevice, a user interface for electronic creation, configuration,simulation, optimization, management, pricing, quoting and displaying ofa virtual SPV or SPV/S system via business logic, logic rules andworkflows that help enhance application engagement, automate theselection and configuration process and minimize errors and illogicalchoices.

According to one aspect, the rules and workflows can be: rules-basedlogic, constraint-based logic, or scenario-based logic.

According to another aspect, a detailed bill of materials (BOM), whichcan include array, lines, disconnects, solar inverter, and rackingstyles is automatically generated for the configured PVS system.

According to another aspect, draft one-line or three-line electricaldrawings are automatically generated based on the configured virtual SPVor SPV/S system and installation choices.

According to another aspect, a quasi-static time-series power flowsimulation model of the configured SPV/S system is automaticallygenerated.

According to another aspect, a static “snap-shot” power flow simulationmodel of the configured PVS/S system is automatically generated.

According to another aspect, a static “snap-shot” power flow simulationof the configured PVS/S system is performed to obtain power flowConstraints for physical and operational boundaries.

According to another aspect, time-varying or quasi-static time-seriespower flow simulation of the configured virtual SPV or SPV/S system isperformed to obtain power flow Constraints for physical and operationalboundaries for one year at various time step resolutions (e.g. every 15minutes for 1 year or every 1 hour for 1 year). For example, for anannual simulation at 1-hour resolution, 8,760 time-steps are simulatedand analyzed. The time-varying atmospheric data model, which includesannual solar irradiance and temperature data at certain time-steps (e.g.every hour of every day for a year), along with the solar PV technologyperformance, efficiency and power output ratings (Solar PV Panel DCOutput Rating in Kilowatts (kW), Solar PV system inverter rating inKilo-Volt-Amps (KVA), Solar PV Technology Power to Efficiency Curve,Solar PV Technology Temperature to and Power Curve provide the powerflow simulation model for determining, via time-series power flowanalysis, the electrical power output for the size of Solar PVtechnology being configured by the user.

According to another aspect, the optimization technique can be based onsimulation model and method with: pre-defined set of rules with only onepossible output per input. The objective is to find the optimalcombination of technology to supply of all energy services required atthe property under consideration, while optimizing the energy flows tominimize costs and/or CO2 emissions. The time-varying atmospheric datamodel, which includes annual solar irradiance and temperature data atcertain time-steps (e.g. every hour of every day for a year), along withthe solar PV technology performance, efficiency and power output ratings(Solar PV Panel DC Output Rating in Kilowatts (kW), Solar PV systeminverter rating in Kilo volt amps (KVA), Solar PV Technology Power toEfficiency Curve, and Solar PV Technology Temperature to Power Curve)provide the simulation model required for determining the electricalpower output for the size of solar PV technology being configured by theuser at their property location. That is, solar panel temperatureaffects the power output potential of the solar PV system. Coldtemperatures generate the most power output, while warmer temperaturesproduce less power output from solar PV technology. Moreover, the lowerthe power output from the solar PV panel, generally the less efficientit will operate.

This data model, along with the Objective Function, Constraints datamodel, and Costs and Loads data model inform the optimization enginewhich then calculates the most cost-optimal size for the solar PVtechnology. This method provides rapid sizing optimization, but islimited in scope to solar PV technology and is unable to calculatestorage system size and dispatch accurately.

According to another aspect, the optimization technique can be based ona physically-based economic optimization model and Mixed Integer LinearProgram (MILP) method. The objective is to find the optimal combinationof technology and operation schedule (dispatch) to supply of all energyservices required at the property under consideration, while optimizingthe energy flows to minimize costs and/or CO2 emissions. Thetime-varying atmospheric data model, which includes annual solarirradiance and temperature data at certain time-steps (e.g. every hourof every day for a year), along with the solar PV technologyperformance, efficiency and power output ratings (Solar PV Panel DCOutput Rating in Kilowatts (kW), Solar PV system inverter rating inKilo-Volt-Amps (KVA), Solar PV Technology Power to Efficiency Curve,Solar PV Technology Temperature to and Power Curve) inform the powerflow simulation model that is used to perform quasi-static time-seriespower flow analysis and calculate the electrical power output for thesize of Solar PV technology being configured by the user. This datamodel, along with the Objective Function, Constraints data model, andCosts and Loads data model inform the MILP optimization engine whichthen calculates the most cost-optimal size for the solar PV with Storagetechnology selected.

Storage technologies can include lithium ion batteries, ice storagesystems, flow batteries and other energy storage systems. If the userhas selected SPV or SPV/S technology to configure, then the optimizationengine calculates the most cost-optimal size for both solar PV andStorage, and also computes the operation logic (dispatch) for thestorage technology. That is, the optimal size of solar PV and theoptimal size of storage are calculated, along with the annual chargingand discharging schedule for the storage system. The schedule to chargeand discharge stored energy is referred to as the dispatch curve whichis in Per Unit format, with 1.0 indicating 100% discharging state and−1.0 indicating 100% discharging state. This method provides highaccuracy and requires additional computation time by the server due tothe complexity of the problem space.

According to another aspect, a method for advertising messaging and leadgeneration can comprise of: a cloud computing Smart Solar Configuratorthat provides a user who is a buyer and a user who is an advertiseraccess to quoting and sales communications. The user who is a buyer caninvite advertisers to offer quotes on her configured virtue SPV or SPV/Ssystem. The buyer can also share configuration data, BOM, Costs, andLoads data with the advertisers and use analysis and simulation featuresto validate the benefits and value of any additions or modifications theadvertisers recommend.

According to another aspect, a method for advertising and contentmarketing messaging and lead generation can comprise of: a cloudcomputing Smart Solar Configurator application that provides a user whois a buyer and a user who is a manufacturer access to sales andadvertising communication. The user who is a manufacturer can offertargeted incentives to the buyer during the virtual SPV or SPV/Sconfiguration process to influence purchase decisions. The buyer canalso share configuration, BOM, Costs and Load data with the manufacturerto get advice on options and technologies. The manufacturer cancommunicate product differentiation and demonstrate benefitscollaboratively with the buyer.

In some implementations, a method comprises: providing, by a servercomputer, an interactive Smart Solar Configurator, pricing and quotingenvironment for selecting, analyzing and simulating a virtual SPV orSPV/S system; providing, by the server computer, a collaborativeinterface in the interactive configurator environment for allowing usersto share a configuration, the collaborative interface configured toallow the users access, using client devices in communication with theserver device, a copy of a shared configuration maintained by the serverdevice, and to edit the shared configuration; and providing, by theserver computer, user interface elements that are selectable by theusers on their respective client devices to perform an analysis orsimulation of the shared configuration and share the results of theanalysis or simulation in the collaborative interface.

Example Server Architecture

FIG. 5 is a block diagram of example computer architecture forimplementing the features and processes described in reference to FIGS.1-4, according to an embodiment. Other architectures are possible,including architectures with more or fewer components. In someimplementations, architecture 500 includes one or more processor(s) 502(e.g., dual-core Intel® Xeon® Processors), one or more networkinterface(s) 506, one or more storage device(s) 504 (e.g., hard disk,optical disk, flash memory) and one or more computer-readable medium(s)508 (e.g., hard disk, optical disk, flash memory, etc.). Thesecomponents can exchange communications and data over one or morecommunication channel(s) 510 (e.g., buses), which can utilize varioushardware and software for facilitating the transfer of data and controlsignals between components.

The term “computer-readable medium” refers to any medium thatparticipates in providing instructions to processor(s) 502 forexecution, including without limitation, non-volatile media (e.g.,optical or magnetic disks), volatile media (e.g., memory) andtransmission media. Transmission media includes, without limitation,coaxial cables, copper wire and fiber optics.

Computer-readable medium(s) 508 can further include operating systeminstructions 512 (e.g., Mac OS® server, Windows® NT server), networkcommunication module instructions 514 and smart solar configuratorinstructions 516 for implementing the features and process described inreference to FIGS. 1-4.

Operating system 512 can be multi-user, multiprocessing, multitasking,multithreading, real time, etc. Operating system 512 performs basictasks, including but not limited to: recognizing input from andproviding output to devices 502, 504, 506 and 508; keeping track andmanaging files and directories on computer-readable medium(s) 508 (e.g.,memory or a storage device); controlling peripheral devices; andmanaging traffic on the one or more communication channel(s) 510.Network communications module 514 includes various components forestablishing and maintaining network connections (e.g., software forimplementing communication protocols, such as TCP/IP, HTTP, etc.).

Architecture 500 can be included in any computer device, including oneor more server computers in a local or distributed network each havingone or more processing cores. Architecture 500 can be implemented in aparallel processing or peer-to-peer infrastructure or on a single devicewith one or more processors. Software can include multiple softwarecomponents or can be a single body of code.

Particular implementations disclosed herein provide one or more of thefollowing advantages. A cloud computing Smart Solar Configuratorprovides a key innovation toward addressing customer acquisition costsfor the solar industry by integrating capabilities never beforecombined, and delivering them via an engaging on-line experience thatinforms and creates consumer excitement without complexity. The SmartSolar Configurator leverages multiple existing data sources, coupledwith SPV and SPV/S economic optimization and sizing analytics (typicallyinaccessible by non-power system engineering experts) to deliver afirst-of-a-kind “Smart Solar Configurator” that enables the generalpublic and solar shoppers from all backgrounds with the tools they needto automatically determine the most optimal SPV or SPV/S system size fortheir home or business, along with an interactive configurator thatgives them the freedom to explore, and choose options and accessoriesthat are compatible with the make, model and size of system they wish topurchase.

Just as consumers can easily research, explore, and configure optionsincluding accessories for cars, PCs, and laptops by make and model, witha cloud computing Smart Solar Configurator shoppers will, for the firsttime ever, have a similar product decision tool, powered by advancedsimulation and DER sizing and optimization technologies, coupled withthe information and pricing transparency they have become conditioned toand expect from durable consumer goods purchasing experiences.

Solar customers will be empowered with accurate upfront system costestimates for an optimally sized PV system that will include a range oftypical installation fees for the model and options selected, and seehow different options and features impact their configured systempricing and return on investment time-line in real-time as they exploreand configure systems—all before deciding to be contacted by aninstaller.

Solar installers and project developers operate in a highly competitivemarket in which access to customers and informed solar system pricingare essential to installer profitability. A cloud computing Smart SolarConfigurator will benefit installers and dealers by attracting informed,in-market consumers in a cost-effective and accountable manner thathelps them sell more solar systems profitably. Moreover, a cloudcomputing Smart Solar Configurator can increase the trust betweeninstallers and solar buyers, which will help dealers increase volume andreduce customer acquisition costs.

Solar equipment manufacturers benefit from a cloud computing Smart SolarConfigurator by offering targeted incentives to consumers, allowingmanufacturers to focus their customer acquisition efforts through adirect marketing channel. The ability to deliver focused incentivesenables manufacturers to reach consumers that might otherwise purchase asolar system from a competing manufacturer.

A cloud computing Smart Solar Configurator addresses concerns forelectrical utility distribution system planners with determining theimpact of residential and non-residential PV on the macro-grid. This caninclude feeder hosting capacity to more detailed deep circuit power flowstudies. A cloud computing Smart Solar Configurator delivers toutilities an open-source data package that includes all the informationnecessary for system planners to update their circuit models and achievea more efficient interconnection and permitting process.

The features described herein may be implemented in digital electroniccircuitry or in computer hardware, firmware, software, or incombinations of them. The features may be implemented in a computerprogram product tangibly embodied in an information carrier, e.g., in amachine-readable storage device, for execution by a programmableprocessor; and method steps may be performed by a programmable processorexecuting a program of instructions to perform functions of thedescribed implementations by operating on input data and generatingoutput.

The described features may be implemented advantageously in one or morecomputer programs that are executable on a programmable system includingat least one programmable processor coupled to receive data andinstructions from, and to transmit data and instructions to, a datastorage system, at least one input device, and at least one outputdevice. A computer program is a set of instructions that may be used,directly or indirectly, in a computer to perform a certain activity orbring about a certain result. A computer program may be written in anyform of programming language (e.g., Objective-C, Java), includingcompiled or interpreted languages, and it may be deployed in any form,including as a stand-alone program or as a module, component,subroutine, or other unit suitable for use in a computing environment.

Suitable processors for the execution of a program of instructionsinclude, by way of example, both general and special purposemicroprocessors, and the sole processor or one of multiple processors orcores, of any kind of computer. Generally, a processor will receiveinstructions and data from a read-only memory or a random-access memoryor both. The essential elements of a computer are a processor forexecuting instructions and one or more memories for storing instructionsand data. Generally, a computer may communicate with mass storagedevices for storing data files. These mass storage devices may includemagnetic disks, such as internal hard disks and removable disks;magneto-optical disks; and optical disks. Storage devices suitable fortangibly embodying computer program instructions and data include allforms of non-volatile memory, including by way of example, semiconductormemory devices, such as EPROM, EEPROM, and flash memory devices;magnetic disks such as internal hard disks and removable disks;magneto-optical disks; and CD-ROM and DVD-ROM disks. The processor andthe memory may be supplemented by, or incorporated in, ASICs(application-specific integrated circuits). To provide for interactionwith a user the features may be implemented on a computer having adisplay device such as a CRT (cathode ray tube), LED (light emittingdiode) or LCD (liquid crystal display) display or monitor for displayinginformation to the author, a keyboard and a pointing device, such as amouse or a trackball by which the author may provide input to thecomputer.

One or more features or steps of the disclosed embodiments may beimplemented using an Application Programming Interface (API). An API maydefine on or more parameters that are passed between a callingapplication and other software code (e.g., an operating system, libraryroutine, function) that provides a service, that provides data, or thatperforms an operation or a computation. The API may be implemented asone or more calls in program code that send or receive one or moreparameters through a parameter list or other structure based on a callconvention defined in an API specification document. A parameter may bea constant, a key, a data structure, an object, an object class, avariable, a data type, a pointer, an array, a list, or another call. APIcalls and parameters may be implemented in any programming language. Theprogramming language may define the vocabulary and calling conventionthat a programmer will employ to access functions supporting the API. Insome implementations, an API call may report to an application thecapabilities of a device running the application, such as inputcapability, output capability, processing capability, power capability,communications capability, etc.

A number of implementations have been described. Nevertheless, it willbe understood that various modifications may be made. Elements of one ormore implementations may be combined, deleted, modified, or supplementedto form further implementations. In yet another example, the logic flowsdepicted in the figures do not require the particular order shown, orsequential order, to achieve desirable results. In addition, other stepsmay be provided, or steps may be eliminated, from the described flows,and other components may be added to, or removed from, the describedsystems. Accordingly, other implementations are within the scope of thefollowing claims.

What is claimed is:
 1. A method comprising: generating, by a computingdevice, a base case economic model for a virtual energy system, the basecase economic model based at least in part on a location of the virtualenergy system; generating, by the computing device, an objectivefunction model and one or more constraints for the virtual energysystem; calculating, by the computing device, a size of the virtualenergy system that achieves an objective function described by theobjective function model using the one or more constraints by comparingan economic model of the virtual energy system with the base caseeconomic model; performing, by the computing device, a simulation of thevirtual energy system based on the calculated size; generating, by thecomputing device, a virtual energy system configuration based at leastin part on results of the simulation; and generating, by the computingdevice and based on the virtual energy system, data for building areal-world version of the virtual energy system.
 2. The method of claim1, wherein the virtual energy system is one of a virtual solarphotovoltaics (SPV) system, solar photovoltaics with storage (SPV/S)system, or other distributed energy resources system.
 3. The method ofclaim 1, wherein the objective function model comprises a data model,the one or more constraints technology purchase or energy costs andloads.
 4. The method of claim 3, wherein the data model includestime-varying atmospheric data.
 5. The method of claim 4, wherein thetime-varying atmospheric data includes future forecasted or annularsolar irradiance, temperature data and efficiency and power outputratings for solar panels.
 6. The method of claim 1, wherein the basecase economic model is generated using energy purchased from anelectrical utility to supply a load at rates or tariffs charged by theelectric utility for the location of the virtual energy system.
 7. Themethod of claim 1, wherein the objective function comprises at least oneenergy cost minimization, carbon dioxide emission minimization,resilience improvement, reliability improvement or redundancyimprovement.
 8. The method of claim 1, wherein the objective functionmodel incorporates one or more technologies configured to operate withinone or more physical operating boundaries and one or more financialconstraints.
 9. The method of claim 8, wherein the one or more physicaloperating boundaries include a maximum rated electrical current carryingcapacity of power delivery equipment that make up an electrical circuitof the virtual energy system.
 10. The method of claim 8, wherein the oneor more physical operating boundaries are calculated by the simulationand include at least one of power flow, transient stability, shortcircuit, energy losses or loading of power delivery equipment that makeup an electrical circuit of the virtual energy system.
 11. The method ofclaim 8, wherein the one or more physical operating boundaries includean allowable voltage drop, short circuit, harmonics, reliability, ortransient stability at each node in an electrical network of the virtualenergy system in two-dimensions or three-dimensions.
 12. The method ofclaim 8, wherein the one or more financial constraints include a maximumpayback period or investment time horizon.
 13. The method of claim 1,wherein the data for building a real-world version of the virtual energysystem includes a bill of materials (BOM).
 14. The method of claim 1,further comprising: automatically generating one-line or three-lineelectrical drawings based on the virtual energy system design.
 15. Themethod of claim 1, further comprising: automatically generating a staticsnap-shot, quasi-static, time-series, time-domain, or frequency domainpower system simulation model of the virtual energy system to obtainpower system constraints for the one or more physical operatingboundaries.
 16. The method of claim 1, wherein the objective functioncomprises a combination of technologies to supply energy servicesrequired at the location and to minimize costs or carbon dioxideemissions, improve resilience, improve reliability or improveredundancy.
 17. The method of claim 1, wherein the atmospheric data istime-varying and includes solar irradiance, wind speed, and temperaturedata at specified time-steps.
 18. The method of claim 1, furthercomprising: automatically generating a cost-optimal size for solarpanels, storage technology or other distributed energy technologies; andautomatically generating operation logic or dispatch for the storagetechnology or other distributed energy technologies.
 19. The method ofclaim 1, wherein the simulation is a power flow simulation.
 20. A systemcomprising: one or more processors; memory storing instructions thatwhen executed by the one or more processors, cause the one or moreprocessors to perform operations comprising. generating a base caseeconomic model for a virtual energy system, the base case economic modelbased at least in part on a location of the virtual energy system;generating an objective function model and one or more constraints forthe virtual energy system; calculating a size of the virtual energysystem that achieves an objective function described by the objectivefunction model using the one or more constraints by comparing aneconomic model of the virtual energy system with the base case economicmodel; performing a simulation of the virtual energy system based on thecalculated size; generating a virtual energy system configuration basedat least in part on results of the simulation; and generating, based onthe virtual energy system, data for building a real-world version of thevirtual energy system.